introduction to algorithms

Did not figure in the article reprinted here to add below: http://liuxinglanyue.javaeye.com/admin/blogs/865784 Introduction to Algorithms much thread algorithm version 3 (-) Introduction to Algorithms, 3rd Edition as much as the thread algorithm (b)

Transfer from: http://blog.csdn.net/hoping/archive/2010/02/25/5326354.aspx The main algorithms in this book are sequential algorithms, suitable for running only one instruction at each single-processor computer. In this chapter, we want to turn paral

Medians and Order Statistics ------ Overview Order Statistics: Order statistics, that is ranked the number to find out n bits in the number of i, denoted by ith Medians: The median in the middle is the number of ------ Medians values Assuming all the

Order statistics Problem: Given n elements in an array, find the kth smallest element (rank k). The naive algorithm to solve this problem: sort the array A and return A [k]. If use heap sort or merge sort, requires Theta (nlgn) time. We can do better

How fast can we sort? (Depends on the sorting model: what you can do with the elements) Comparison sorts: only use comparisons to determine relative order of elements: quicksort - Theta (nlgn) randomized version heapsort - Theta (nlgn) merge sort - T

The Lecture includes CLRS in Chapter3-Chapter4 two chapters: Asymptotic Behavior of recursive tag reconciliation. Erik Demaine speaker. Gee! Every time I see Erik for a "hair" with a shaved head, Professor Leiserson wanted to laugh, do not misun

Introduction to Algorithms, MIT OCW 6.046J, Instructors: Prof. Charles Leiserson and Prof. Erik Demaine. Charles Leiserson ( http://people.csail.mit.edu/cel/ ), Introduction to Algorithms is a book on the CLRS in the L, 1975 was awarded Bachelor and